MA 215 at GRCC offers a hands-on, non-calculus introduction to statistics, from probability to ANOVA, with real-world applications across disciplines. Integrated ALEKS and Canvas tools streamline ...

A semester-long study of topics in Statistics. Topics and emphases will vary according to the instructor. This course may be repeated for credit with different topics. See the details in the schedule ...

Foundations of Algebra emphasizes computing with whole numbers and fractions, decimals, and integers; solving word problems with whole numbers, fractions, decimals and integers; solving basic linear ...

Contents: The R programming language is used for statistical data analysis and visualization. R and the R Studio development environment are a globally used tool set for statistical analysis and data ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

This course introduces students to statistics and quantitative information. The course surveys probability theory, hypothesis testing, descriptive statistics and visualizations, and inferential ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

The field of data analytics is developing rapidly. With the rise of ever larger and more specialised datasets, it’s essential to understand how to collect, handle, evaluate and interpret data to ...

Introduction to handling and analysis of digital geospatial data. Operation of GIS software, including collection, processing and understanding of data, production of maps and geospatial projection ...

Course planning information Course notes Access to a Computer with Excel is required. Expected prior learning Students must have a good grounding in basic maths. It is strongly recommended that ...